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Lifelink, a mobile real-time telemonitoring and diagnostic facility, linked by mobile phones, was evaluated. Thirty 2-hour electrocardiogram (ECG) signals from cardiac patients were analyzed using detrended fluctuation analysis. This analysis detects long-range correlations embedded in non-stationary temporal series. The patient population was categorized in three classes: healthy, congestive heart failure, and atrial fibrillation. This system permits a physician to evaluate the mobile phone–based system as a novel approach to analyze ECG at a distance.

Current wired telemedicine systems encounter difficulties when implemented in archipelagic developing countries because of the high cost of fixed infrastructure. In this research, we devised Lifelink, a mobile real-time telemonitoring and diagnostic facility to command and control remote medical devices through mobile phones. The whole process is phone-based, effectively freeing offsite medical specialists from stationary monitoring consoles and endowing the system with the potential to increase the number participating consultants. The electrocardiogram (ECG) readings are analyzed using a detrended fluctuation technique and classified into pathological cases using an unassisted K-means clustering algorithm. We analyzed 30 batches of 2-hour ECG signals taken from cardiac patients (20 males, 10 females, mean age 46.7 years) with pre-diagnosed pathologies. The method successfully categorized the 30 subjects without user intervention into the following cases: normal (at 86.7% accuracy), congestive heart failure (86.7%), and atrial fibrillation (80.0%). The synergy of mobile monitoring and fluctuation analysis presents a powerful platform to reach remote, underserved communities with poor or nonexistent wired communication structures. It is likely to be essential in the development of new mobile diagnostic and prognostic measures.